Interpreting medical tables as linked data for generating meta-analysis reports
| dc.contributor.author | Mulwad, Varish | |
| dc.contributor.author | Finin, Tim | |
| dc.contributor.author | Joshi, Anupam | |
| dc.date.accessioned | 2018-11-02T14:00:12Z | |
| dc.date.available | 2018-11-02T14:00:12Z | |
| dc.date.issued | 2014-08-15 | |
| dc.description | 15th IEEE Int. Conf. on Information Reuse and Integration | en |
| dc.description.abstract | Evidence-based medicine is the application of current medical evidence to patient care and typically uses quantitative data from research studies. It is increasingly driven by data on the efficacy of drug dosages and the correlations between various medical factors that are assembled and integrated through meta-analyses (i.e., systematic reviews) of data in tables from publications and clinical trial studies. We describe a important component of a system to automatically produce evidence reports that performs two key functions: (i) understanding the meaning of data in medical tables and (ii) identifying and retrieving relevant tables given a input query. We present modifications to our existing framework for inferring the semantics of tables and an ontology developed to model and represent medical tables in RDF. Representing medical tables as RDF makes it easier for the automatic extraction, integration and reuse of data from multiple studies, which is essential for generating meta-analyses reports. We show how relevant tables can be identified by querying over their RDF representations and describe two evaluation experiments: one on mapping medical tables to linked data and another on identifying tables relevant to a retrieval query. | en |
| dc.description.sponsorship | This research was supported by NSF awards 1228198, 1250627 and 0910838 and a gift from Microsoft Research. | en |
| dc.description.uri | https://ieeexplore.ieee.org/document/7051955 | en |
| dc.format.extent | 10 pages | en |
| dc.genre | conference papers and proceedings | en |
| dc.identifier | doi:10.13016/M24B2X84S | |
| dc.identifier.citation | Varish Mulwad, Tim Finin and Anupam Joshi, Interpreting Medical Tables as Linked Data to Generate Meta-Analysis Reports, 15th IEEE Int. Conf. on Information Reuse and Integration, IEEE, August 2014, DOI: 10.1109/IRI.2014.7051955 | en |
| dc.identifier.uri | 10.1109/IRI.2014.7051955 | |
| dc.identifier.uri | http://hdl.handle.net/11603/11835 | |
| dc.language.iso | en | en |
| dc.publisher | IEEE | en |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.subject | Hypertension | en |
| dc.subject | Ontologies | en |
| dc.subject | Correlation | en |
| dc.subject | Unified modeling language | en |
| dc.subject | Data mining | en |
| dc.subject | Semantics | en |
| dc.subject | UMBC Ebiquity Research Group | en |
| dc.subject | medical table interpretation | en |
| dc.subject | retrieval query | en |
| dc.subject | Resource description framework | en |
| dc.subject | data integration | en |
| dc.title | Interpreting medical tables as linked data for generating meta-analysis reports | en |
| dc.type | Text | en |